Generative Models
A robotic Michelangelo painting by Dario Cioni
Second year Master’s Course in A.I.
In this course we will cover all about modern deep generative models. We will start from basics on probabilities and deep learning models and then move onto more advanced models. Course material on moodle.
The course will cover:
- Autoregressive Models
- Normalizing Flows
- Latent Variable Models
- Variational Autoencoders
- Diffusion Models
- Generative Adversarial Networks
- Applications: conditional image generation; text generation; multimodal generation
Lorenzo Seidenari
Assistant Professor of Computer Engineering
I am an Associate Professor (Tenure Track) of Computer Engineering at the University of Florence working on Deep Learning and Computer Vision.